Investigating the chemical composition of materials is important for fully understanding their material properties. Often, chemical heterogeneity at the micro- to nanoscale influences the macroscopic behavior of materials. For these types of samples, SEM-EDS is ideal.
Scanning Electron Microscopy (SEM) can be used in tandem with Energy Dispersive X-ray Spectroscopy (EDS) to better understand material properties. At its core, SEM uses a high-energy electron beam to characterize samples at the micro- to nanoscale, offering higher resolution and depth of field than other microscopy techniques. Secondary and backscattered electrons generated by interactions between the electron beam and sample can be used to characterize surface morphology and composition respectively. Similarly, characteristic X-rays generated by the sample can be analyzed to assess its composition.
Characteristic X-rays are emitted when outer orbital electrons within an atom relax to fill lower-energy vacancies within inner orbitals created by a high-energy source such as an electron beam. Both the energy and wavelength of these X-rays are unique to the element they are generated from. While multiple techniques exist to analyze these X-rays, perhaps the most common to pair with SEM is EDS. At their core, EDS detectors analyze the chemical composition of materials by counting the X-rays being generated and measuring each X-ray’s energy to determine what element it came from.
EDS detectors are prized for their speed, versatility and ease of use. They allow users to quickly assess what elements are present in a sample and estimate the relative abundances, often in near-real time and without destroying the sample. We often visualize EDS data as a spectrum, showing X-ray energy vs. number of X-rays analyzed (intensity). Interpreting this spectrum and how it is transposed into chemical compositions is critical for accurately characterizing materials.
Although technologic advancements such as automatic element identification, peak deconvolution and quantification have vastly simplified interpreting EDS data, it is still important to understand the principles and best practices of SEM-EDS. This basic understanding empowers users to feel confident about their SEM-EDS results and consistently collect the best chemical data possible.
Read on to learn more detail about how to interpret and utilize an SEM-EDS spectrum.
When irradiated by a high-energy source such as an electron beam, every element emits a set of X-rays with unique energies and wavelengths, hence, “characteristic X-rays”. Modern state-of-the-art SEM-EDS detectors can analyze X-rays ranging in energy from tens of electron volts (eV) to tens of kiloelectron volts (keV), allowing users to characterize nearly every element between Li and U. Most standard EDS systems are optimized for analyzing Be or B through U.
As shown in Figure 1 below, we visualize EDS data as a spectrum, plotting X-ray energy versus intensity. The peak intensity corresponds to the element’s relative abundance in the sample, while the width of each peak corresponds to the energy resolution of the EDS detector, typically 125-132 eV (FWHM at Mn-Kα).
Modern SEM-EDS software is designed to automatically identify X-ray peaks by comparing their shape and energy to a known database. This allows users of all skill levels to readily collect EDS data. However, for minor or trace (~0.1-5 wt%) elements, the software may be unable to distinguish the peak from the background radiation (Bremsstrahlung). In this case, users may need to manually examine the spectrum to confirm the element's presence. Similarly, some X-ray peaks overlap within the uncertainty of the method, requiring software peak deconvolution. While this method is robust for even severe peak overlaps (e.g., Ti-Ba or W-Si), users should be aware of what peak overlaps to expect for their sample to ensure they are adequately accounted for.
SEM-EDS is used both for providing qualitative information about the elements present and as a semi-quantitative analysis technique. To accurately quantify elemental concentrations, considerations such as the homogeneity, thickness, and surface topography of the sample are essential. These factors influence the accuracy of the quantitative results.
While there are multiple approaches for calculating the sample composition from an EDS spectrum, the simplest and most widely utilized is standardless quantitative analysis. This method compares the relative intensities of all of the identified peaks, normalizing the results to 100%. A matrix correction (e.g., ZAF, Φρz) is applied to account for variations in X-ray yield efficiency as a function of composition. For an ideal sample, this method is reproducible within ±2% to ±5% for major components.
Alternatively, some users may choose to calculate quantitative results using standards. In this case, the peak intensity of each element present in the sample is compared to that of a standard. A matrix correction is still applied. While this approach in principle yields more accurate quantitative results, it relies more heavily on ideal sample preparation and is far more susceptible to user error.
3. Sample Preparation
The quality of SEM-EDS analysis is highly dependent on sample preparation. The sample should be polished, flat, and homogeneous relative to the interaction volume of the electron beam to ensure accurate chemical analysis. For samples with non-uniform composition, acquiring spectra from multiple areas or acquiring a hyperspectral EDS map can help assess heterogeneity.The quality of SEM-EDS analysis is highly dependent on sample preparation. The sample should be polished, flat, and homogeneous relative to the interaction volume of the electron beam to ensure accurate chemical analysis. For samples with non-uniform composition, acquiring spectra from multiple areas or acquiring a hyperspectral EDS map can help assess heterogeneity.
4. Consideration of Topography
The topography of a sample can significantly affect SEM-EDS analysis. Rough or irregular surfaces may preferentially absorb or block X-rays, leading to errors in calculated composition. Positioning the sample to provide a direct line of sight between the region of interest is crucial and can assist in fully characterizing the sample, though quantitative results should be treated with caution.
5. Accelerating Voltage
The choice of accelerating voltage is critical for the excitation of X-ray lines of elements in the sample. A voltage 1.5 to 2 times higher than the energy of the X-ray lines from the element(s) of interest is recommended to efficiently excite the element. For unknown samples, using an accelerating voltage between 15 kV and 20 kV ensures that all elements present are identified. However, users might choose to collect EDS data at lower accelerating voltages to minimize interaction volume, especially to aid in characterization of small nano- to micro-scale features.
6. Hyperspectral EDS Mapping
Modern EDS systems offer advanced features like acquiring hyperspectral EDS maps, enabling the detailed characterization of chemically heterogeneous samples. Rather than acquiring an EDS spectrum at a single point, hyperspectral maps are more akin to SEM images, where every pixel in the image represents an individual EDS spectrum. This technique is powerful for understanding the distribution of elements in a sample, allowing identification and full characterization of discrete layers, phases or chemical gradients. The ability to treat each pixel as a quantitative analysis by leveraging
quantitative mapping (QMap) allows samples even with complex matrices to be studied. This makes the technique invaluable for studying samples with:
● Complex compositions
● Overlapping peaks
● Minor/trace elements with low peak/background ratios
Final Thoughts on the SEM-EDS Spectrum
With a basic understanding of the principles of SEM-EDS, researchers and analysts can effectively acquire and interpret robust EDS data. This can unlock valuable quantitative and qualitative insights into their samples.
It is crucial to consider the limitations and challenges associated with SEM-EDS analysis, including sample preparation and the potential for quantitative errors. However, with a careful approach and interpretation, SEM-EDS remains an indispensable tool in materials science and engineering for elemental analysis at the micro- to nano scale.
JEOL USA’s Tools Incorporate the SEM-EDS Spectrum
SEM-EDS analyses are fast, effective, and can help interrogate a wide range of material properties and characteristics. Understanding what EDS spectra are and how they can be used to inform qualitative and semi-quantitative chemical analysis of samples is essential for accurately interpreting and gaining the most out of this type of analysis.
SEM-EDS can provide powerful information about the material properties at the micro- to nanoscale. It is therefore utilized for with a variety of materials such as:
● Polymers
● Metals
● Ceramics
● Composites
● Batteries
● Pharmaceuticals
● Rocks and minerals
● Forensics
● Electronics and semiconductors
Chemical analysis of these materials by SEM-EDS can be leveraged across industry, government and academic sectors for wide range of applications spanning from investigating the chemical composition of minerals in meteorites to fingerprinting forensic samples to developing next-generation energy storage solutions and beyond.
If you are looking for an innovative SEM-EDS tool or analytical technique to help you with your research, we, JEOL USA, would recommend browsing our website.
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